★ From “how to use” to “commercial application” – a deep dive into Stable Diffusion with a complete step‑by‑step teaching process.
★ Covers mainstream scenarios such as commercial photography, product design, advertising creativity, and photo restoration.
★ 36 real‑world case studies break down every operation, including parameters, prompts, and model merging techniques.
★ Suitable for AI enthusiasts as well as professionals who want to learn how to monetize AI.

This is a professional book that enables readers to easily master AI painting technology.
It introduces Stable Diffusion – the AI painting powerhouse – from “how to deploy Stable Diffusion” to “how to use LoRA models to design plush toys,” sharing the author’s practical artistic creation experience. The content covers the complete workflow from basic deployment and prompt grammar to model merging and ControlNet extensions, with detailed guidance on hardware requirements and model classification. Special emphasis is placed on the practicality of parameter settings and operation steps, accompanied by video tutorials and interface layout diagrams. The book is suitable for absolute beginners to get started quickly, while also offering advanced users high‑level techniques such as model merging and dynamic prompt expansion, forming a complete knowledge loop from basics to advanced to real‑world practice.

Shanzhu AIGC Team – Led by Mr. Li Yan, design director of a China Top‑10 4A advertising agency, the team brings together industry elites and senior experts with deep knowledge and rich hands‑on experience in the AIGC field. The team focuses on providing high‑quality courses and professional training covering cutting‑edge technologies such as Stable Diffusion, ComfyUI, and LoRA, aiming to help learners master the essential skills of AIGC.

Chapter 1: Overview of AI Painting
1.1 Origin and Development of AI Painting
1.2 Applications and Prospects of AI Painting
1.3 Common AI Painting Tools

Chapter 2: Stable Diffusion Basics
2.1 Deployment and Hardware Requirements
2.2 Model Classification
2.3 Installation
2.4 Interface and Layout

Chapter 3: Prompts
3.1 Types of Prompts
3.2 Prompt Weights
3.3 Prompt Syntax
3.4 Prompt Presets and Artist Styles

Chapter 4: Upscaling, Restoration, and Inpainting
4.1 High‑Resolution Fix
4.2 ADetailer (Face/Hand Restoration)
4.3 Tiled Diffusion & Tiled VAE
4.4 Post‑Processing
4.5 Ultimate SD Upscale
4.6 Inpainting
4.7 PNG Info

Chapter 5: LoRA Model Applications
5.1 General LoRA Models (12 practical cases)
5.2 Style LoRA Models (17 practical cases)

Chapter 6: ControlNet Extensions
6.1 ControlNet Interface
6.2 Line‑type Control (Canny, Lineart, SoftEdge, Scribble, MLSD)
6.3 Surface‑type Control (Depth, NormalMap)
6.4 Style Transfer (IP‑Adapter, Recolor)
6.5 Pose & Face Swap (OpenPose, Instant‑ID)
6.6 Inpainting & Tiling (Inpaint, Tile)

Chapter 7: Other Extensions
7.1 Installing, Updating, Uninstalling Extensions
7.2 Dynamic Prompts Extension
7.3 Segment Anything Extension
7.4 LoRA Block Weight

Chapter 8: Commercial Practice Cases
8.1 Commercial Photography (ID photos, artistic portraits, old photo restoration, historical figure reconstruction)
8.2 Product Design (traditional design, plush toy design, creative figures)
8.3 Interior & Architectural Design (interior design, architectural design)
8.4 Advertising Creativity (seasonal poster design, commercial poster design)
8.5 Relief Design (line art to depth map, photo to depth map, 3D model to depth map)

Chapter 9: Model Merging
9.1 Checkpoint Model Merging
9.2 LoRA Model Merging

Chapter 10: Stable Diffusion Settings and Use of Supplementary Materials
10.1 The “Settings” Tab
10.2 Supplementary Resources